Production Control in Underground Mines using Discrete EventSimulation

The optimization of production has come a long way in the last few years. From having to implement new production philosophies directly into the production, today you can simply build a simulation on the computer that can be used to test new solutions. This makes it cheaper and less time-consuming to improve production. This report will describe the thesis work made by two students from Lulea University of Technology studying mechanical engineering with orientation production technology. The thesis work was made at Boliden MineralsAB during the spring term of 2021. This master thesis aim is to look at the potential of using discrete-event simulation as a tool to test different production philosophies. To do this, a simulation model is built to represent Boliden’s mining operation. The focus will be on the Cut and fill process, and how vehicles and operators are dispatched. From interviews, videos and information gave by Boliden a current state analysis was done to get a good understanding of the situation and how the process works. This combined with a litterateur study a good foundation was made to start building the simulation. Since this is the first time Boliden uses simulation on the cut and fill process in this manner, there’s been close contact with Boliden to validate and verify the models. The different production scenarios that were simulated were selected with the guidance of Boliden to look at the most relevant areas for them. Firstly, a base model was constructed, this model had a number of restrictions compared to the real-life process. With data from previous work that Boliden had with simulation models, the base model could be controlled that it worked properly. From this model others, models could be build-up, with the difference of using another production control philosophy for the simulation. By using these philosophies there could be determined an increase by 1% in productivity when prioritizing operators to the bottleneck of the process to maximize utilization